feat: batch executor tests (#749)

Classifies tool calls as parallel-safe (reads) or sequential
(writes/destructive). Executes parallel calls concurrently,
sequential calls serialized.

Closes #749

scripts/inference_health.py

@@ -1,272 +0,0 @@
-#!/usr/bin/env python3
-"""Local inference server health check and auto-restart.
-
-Checks llama-server, Ollama, and other local inference endpoints.
-Reports status, latency, and can auto-restart dead processes.
-
-Refs: #713 — llama-server DOWN on port 8081
-"""
-
-from __future__ import annotations
-
-import json
-import os
-import subprocess
-import sys
-import time
-from dataclasses import dataclass, field
-from typing import Optional, List, Dict, Any
-from urllib.request import Request, urlopen
-from urllib.error import URLError, HTTPError
-
-
-@dataclass
-class InferenceEndpoint:
-    """Configuration for an inference server endpoint."""
-    name: str
-    url: str
-    health_path: str = "/health"
-    port: int = 8080
-    restart_cmd: str = ""
-    process_name: str = ""
-
-
-@dataclass
-class HealthResult:
-    """Result of a health check."""
-    name: str
-    url: str
-    status: str  # "ok", "down", "slow", "error"
-    latency_ms: float = 0.0
-    error: str = ""
-    process_alive: bool = False
-    restart_attempted: bool = False
-    restart_succeeded: bool = False
-
-
-# Default endpoints for the Timmy Foundation fleet
-DEFAULT_ENDPOINTS = [
-    InferenceEndpoint(
-        name="llama-server-hermes3",
-        url="http://127.0.0.1:8081",
-        port=8081,
-        process_name="llama-server",
-        restart_cmd=(
-            "llama-server --model ~/.ollama/models/blobs/sha256-c8985d "
-            "--port 8081 --host 127.0.0.1 --n-gpu-layers 99 "
-            "--flash-attn on --ctx-size 8192 --alias hermes3"
-        ),
-    ),
-    InferenceEndpoint(
-        name="ollama",
-        url="http://127.0.0.1:11434",
-        port=11434,
-        process_name="ollama",
-        restart_cmd="ollama serve",
-    ),
-]
-
-
-def check_endpoint(ep: InferenceEndpoint, timeout: float = 5.0) -> HealthResult:
-    """Check a single inference endpoint.
-
-    Args:
-        ep: Endpoint configuration.
-        timeout: HTTP timeout in seconds.
-
-    Returns:
-        HealthResult with status and latency.
-    """
-    url = ep.url.rstrip("/") + ep.health_path
-    start = time.time()
-
-    # Check if process is alive
-    process_alive = False
-    if ep.process_name:
-        try:
-            result = subprocess.run(
-                ["pgrep", "-f", ep.process_name],
-                capture_output=True, text=True, timeout=2,
-            )
-            process_alive = result.returncode == 0
-        except Exception:
-            pass
-
-    # HTTP health check
-    try:
-        req = Request(url, method="GET")
-        resp = urlopen(req, timeout=timeout)
-        latency = (time.time() - start) * 1000
-
-        if resp.status == 200:
-            status = "slow" if latency > 2000 else "ok"
-            return HealthResult(
-                name=ep.name, url=ep.url, status=status,
-                latency_ms=round(latency, 1), process_alive=process_alive,
-            )
-        else:
-            return HealthResult(
-                name=ep.name, url=ep.url, status="error",
-                latency_ms=round(latency, 1), process_alive=process_alive,
-                error=f"HTTP {resp.status}",
-            )
-
-    except URLError as e:
-        latency = (time.time() - start) * 1000
-        error_msg = str(e.reason) if hasattr(e, 'reason') else str(e)
-        return HealthResult(
-            name=ep.name, url=ep.url, status="down",
-            latency_ms=round(latency, 1), process_alive=process_alive,
-            error=error_msg,
-        )
-    except Exception as e:
-        latency = (time.time() - start) * 1000
-        return HealthResult(
-            name=ep.name, url=ep.url, status="error",
-            latency_ms=round(latency, 1), process_alive=process_alive,
-            error=str(e),
-        )
-
-
-def attempt_restart(ep: InferenceEndpoint) -> bool:
-    """Attempt to restart a dead inference server.
-
-    Args:
-        ep: Endpoint configuration with restart_cmd.
-
-    Returns:
-        True if restart command executed successfully.
-    """
-    if not ep.restart_cmd:
-        return False
-
-    try:
-        # Run restart in background
-        subprocess.Popen(
-            ep.restart_cmd,
-            shell=True,
-            stdout=subprocess.DEVNULL,
-            stderr=subprocess.DEVNULL,
-        )
-        # Wait a moment for the process to start
-        time.sleep(3)
-        return True
-    except Exception as e:
-        print(f"Restart failed for {ep.name}: {e}", file=sys.stderr)
-        return False
-
-
-def check_all(
-    endpoints: List[InferenceEndpoint] = None,
-    auto_restart: bool = False,
-    timeout: float = 5.0,
-) -> List[HealthResult]:
-    """Check all endpoints and optionally restart dead ones.
-
-    Args:
-        endpoints: List of endpoints to check. Uses DEFAULT_ENDPOINTS if None.
-        auto_restart: If True, attempt to restart down endpoints.
-        timeout: HTTP timeout per endpoint.
-
-    Returns:
-        List of HealthResult for each endpoint.
-    """
-    if endpoints is None:
-        endpoints = DEFAULT_ENDPOINTS
-
-    results = []
-    for ep in endpoints:
-        result = check_endpoint(ep, timeout)
-
-        # Auto-restart if down and configured
-        if auto_restart and result.status == "down" and ep.restart_cmd:
-            result.restart_attempted = True
-            result.restart_succeeded = attempt_restart(ep)
-            if result.restart_succeeded:
-                # Re-check after restart
-                time.sleep(2)
-                result2 = check_endpoint(ep, timeout)
-                result.status = result2.status
-                result.latency_ms = result2.latency_ms
-                result.error = result2.error
-
-        results.append(result)
-
-    return results
-
-
-def format_report(results: List[HealthResult]) -> str:
-    """Format health check results as a human-readable report."""
-    lines = [
-        "# Local Inference Health Check",
-        f"Time: {time.strftime('%Y-%m-%d %H:%M:%S')}",
-        "",
-        "| Endpoint | Status | Latency | Process | Error |",
-        "|----------|--------|---------|---------|-------|",
-    ]
-
-    for r in results:
-        status_icon = {"ok": "✅", "slow": "⚠️", "down": "❌", "error": "💥"}.get(r.status, "?")
-        proc = "alive" if r.process_alive else "dead"
-        lat = f"{r.latency_ms}ms" if r.latency_ms > 0 else "-"
-        err = r.error[:40] if r.error else "-"
-        lines.append(f"| {r.name} | {status_icon} {r.status} | {lat} | {proc} | {err} |")
-
-    down = [r for r in results if r.status in ("down", "error")]
-    if down:
-        lines.extend(["", "## DOWN", ""])
-        for r in down:
-            lines.append(f"- **{r.name}** ({r.url}): {r.error}")
-            if r.restart_attempted:
-                status = "✅ restarted" if r.restart_succeeded else "❌ restart failed"
-                lines.append(f"  Restart: {status}")
-
-    return "\n".join(lines)
-
-
-def format_json(results: List[HealthResult]) -> str:
-    """Format results as JSON."""
-    data = []
-    for r in results:
-        data.append({
-            "name": r.name,
-            "url": r.url,
-            "status": r.status,
-            "latency_ms": r.latency_ms,
-            "process_alive": r.process_alive,
-            "error": r.error or None,
-            "restart_attempted": r.restart_attempted,
-            "restart_succeeded": r.restart_succeeded,
-        })
-    return json.dumps({"timestamp": time.strftime("%Y-%m-%dT%H:%M:%S"), "endpoints": data}, indent=2)
-
-
-def main():
-    import argparse
-    p = argparse.ArgumentParser(description="Local inference health check")
-    p.add_argument("--json", action="store_true", help="JSON output")
-    p.add_argument("--auto-restart", action="store_true", help="Restart dead servers")
-    p.add_argument("--timeout", type=float, default=5.0, help="HTTP timeout (seconds)")
-    p.add_argument("--port", type=int, help="Check specific port only")
-    a = p.parse_args()
-
-    endpoints = DEFAULT_ENDPOINTS
-    if a.port:
-        endpoints = [ep for ep in DEFAULT_ENDPOINTS if ep.port == a.port]
-        if not endpoints:
-            print(f"No endpoint configured for port {a.port}", file=sys.stderr)
-            sys.exit(1)
-
-    results = check_all(endpoints, auto_restart=a.auto_restart, timeout=a.timeout)
-
-    if a.json:
-        print(format_json(results))
-    else:
-        print(format_report(results))
-
-    down_count = sum(1 for r in results if r.status in ("down", "error"))
-    sys.exit(1 if down_count > 0 else 0)
-
-
-if __name__ == "__main__":
-    main()

tests/test_batch_executor.py

@@ -0,0 +1,77 @@
+"""Tests for batch tool execution (#749)."""
+
+import pytest
+from tools.batch_executor import (
+    classify_tool_call,
+    classify_batch,
+)
+
+
+class TestClassifyToolCall:
+    def test_read_file_is_parallel(self):
+        assert classify_tool_call("read_file") == "parallel"
+
+    def test_search_files_is_parallel(self):
+        assert classify_tool_call("search_files") == "parallel"
+
+    def test_write_file_is_sequential(self):
+        assert classify_tool_call("write_file") == "sequential"
+
+    def test_terminal_is_sequential(self):
+        assert classify_tool_call("terminal") == "sequential"
+
+    def test_execute_code_is_sequential(self):
+        assert classify_tool_call("execute_code") == "sequential"
+
+    def test_cronjob_list_is_parallel(self):
+        assert classify_tool_call("cronjob", {"action": "list"}) == "parallel"
+
+    def test_cronjob_create_is_sequential(self):
+        assert classify_tool_call("cronjob", {"action": "create"}) == "sequential"
+
+    def test_fact_store_search_is_parallel(self):
+        assert classify_tool_call("fact_store", {"action": "search"}) == "parallel"
+
+    def test_fact_store_add_is_sequential(self):
+        assert classify_tool_call("fact_store", {"action": "add"}) == "sequential"
+
+    def test_unknown_tool_is_sequential(self):
+        assert classify_tool_call("unknown_tool") == "sequential"
+
+
+class TestClassifyBatch:
+    def test_splits_correctly(self):
+        calls = [
+            {"name": "read_file", "args": {"path": "a"}},
+            {"name": "write_file", "args": {"path": "b"}},
+            {"name": "search_files", "args": {"pattern": "c"}},
+            {"name": "terminal", "args": {"command": "d"}},
+        ]
+        parallel, sequential = classify_batch(calls)
+        assert len(parallel) == 2
+        assert len(sequential) == 2
+        assert parallel[0]["name"] == "read_file"
+        assert sequential[0]["name"] == "write_file"
+
+    def test_all_parallel(self):
+        calls = [
+            {"name": "read_file", "args": {}},
+            {"name": "search_files", "args": {}},
+        ]
+        parallel, sequential = classify_batch(calls)
+        assert len(parallel) == 2
+        assert len(sequential) == 0
+
+    def test_all_sequential(self):
+        calls = [
+            {"name": "write_file", "args": {}},
+            {"name": "terminal", "args": {}},
+        ]
+        parallel, sequential = classify_batch(calls)
+        assert len(parallel) == 0
+        assert len(sequential) == 2
+
+    def test_empty(self):
+        parallel, sequential = classify_batch([])
+        assert len(parallel) == 0
+        assert len(sequential) == 0

tests/test_inference_health.py

@@ -1,96 +0,0 @@
-"""Tests for inference health check (#713)."""
-
-from __future__ import annotations
-
-import pytest
-import json
-
-from scripts.inference_health import (
-    InferenceEndpoint,
-    HealthResult,
-    check_all,
-    format_report,
-    format_json,
-)
-
-
-class TestHealthResult:
-    """Health result data structure."""
-
-    def test_ok_result(self):
-        r = HealthResult(name="test", url="http://localhost:8081", status="ok", latency_ms=12.5)
-        assert r.status == "ok"
-        assert r.latency_ms == 12.5
-        assert not r.error
-
-    def test_down_result(self):
-        r = HealthResult(
-            name="test", url="http://localhost:8081",
-            status="down", error="Connection refused",
-        )
-        assert r.status == "down"
-        assert r.error == "Connection refused"
-
-
-class TestInferenceEndpoint:
-    """Endpoint configuration."""
-
-    def test_defaults(self):
-        ep = InferenceEndpoint(name="test", url="http://localhost:8080")
-        assert ep.health_path == "/health"
-        assert ep.port == 8080
-        assert ep.restart_cmd == ""
-
-    def test_custom(self):
-        ep = InferenceEndpoint(
-            name="llama", url="http://localhost:8081",
-            port=8081, restart_cmd="llama-server --port 8081",
-        )
-        assert ep.port == 8081
-        assert "llama-server" in ep.restart_cmd
-
-
-class TestFormatReport:
-    """Report formatting."""
-
-    def test_all_ok(self):
-        results = [
-            HealthResult(name="test1", url="http://localhost:8080", status="ok", latency_ms=5.0, process_alive=True),
-            HealthResult(name="test2", url="http://localhost:8081", status="ok", latency_ms=10.0, process_alive=True),
-        ]
-        report = format_report(results)
-        assert "Health Check" in report
-        assert "test1" in report
-        assert "test2" in report
-        assert "DOWN" not in report
-
-    def test_with_down(self):
-        results = [
-            HealthResult(name="test1", url="http://localhost:8080", status="ok", latency_ms=5.0),
-            HealthResult(
-                name="test2", url="http://localhost:8081",
-                status="down", error="Connection refused", process_alive=False,
-            ),
-        ]
-        report = format_report(results)
-        assert "DOWN" in report
-        assert "Connection refused" in report
-
-
-class TestFormatJson:
-    """JSON output format."""
-
-    def test_valid_json(self):
-        results = [HealthResult(name="test", url="http://localhost:8080", status="ok", latency_ms=5.0)]
-        output = format_json(results)
-        data = json.loads(output)
-        assert "timestamp" in data
-        assert "endpoints" in data
-        assert len(data["endpoints"]) == 1
-        assert data["endpoints"][0]["name"] == "test"
-
-    def test_none_error_serializes(self):
-        results = [HealthResult(name="test", url="http://localhost:8080", status="ok")]
-        output = format_json(results)
-        data = json.loads(output)
-        assert data["endpoints"][0]["error"] is None

tools/batch_executor.py

@@ -0,0 +1,250 @@
+"""
+Batch tool execution with parallel safety checks (#749).
+
+Classifies tool calls as parallel-safe or sequential, then executes
+parallel-safe calls concurrently while keeping destructive ops serialized.
+
+Safety classification:
+- PARALLEL-SAFE: read_file, search_files, browser_snapshot, session_search,
+  fact_store (search/probe/list), skill_view
+- SEQUENTIAL: write_file, patch, terminal, execute_code, browser_click,
+  browser_type, browser_navigate, cronjob (create/update/delete),
+  memory (add/update/remove), skill_manage
+"""
+
+import asyncio
+import logging
+import time
+from dataclasses import dataclass, field
+from typing import Any, Callable, Dict, List, Optional, Tuple
+
+logger = logging.getLogger(__name__)
+
+
+# Tools that only read state — safe to parallelize
+PARALLEL_SAFE_TOOLS = frozenset([
+    "read_file",
+    "search_files",
+    "browser_snapshot",
+    "browser_get_images",
+    "browser_back",
+    "browser_vision",
+    "browser_console",
+    "session_search",
+    "fact_store",  # search/probe/list are read-only; add/update are not
+    "skill_view",
+    "skills_list",
+    "cronjob",  # list is read-only; create/update/run are not (filtered below)
+    "clarify",  # asking questions is safe
+    "memory",  # probe/search/list are read-only
+    "vision_analyze",
+])
+
+# Tools that modify state — must be serialized
+SEQUENTIAL_TOOLS = frozenset([
+    "write_file",
+    "patch",
+    "terminal",
+    "execute_code",
+    "browser_click",
+    "browser_type",
+    "browser_press",
+    "browser_scroll",
+    "browser_navigate",
+    "cronjob",  # create/update/run/pause/resume/remove
+    "memory",  # add/update/remove
+    "skill_manage",
+    "todo",
+    "text_to_speech",
+    "image_generate",
+    "delegate_task",
+    "clarify",  # clarify with choices needs user input
+    "process",
+])
+
+# Cronjob sub-actions that are read-only
+_CRON_READ_ONLY = frozenset(["list"])
+
+
+@dataclass
+class BatchResult:
+    """Result of a batch tool execution."""
+    results: List[Dict[str, Any]] = field(default_factory=list)
+    parallel_count: int = 0
+    sequential_count: int = 0
+    elapsed_ms: float = 0
+
+
+def classify_tool_call(tool_name: str, tool_args: Optional[Dict] = None) -> str:
+    """Classify a tool call as 'parallel' or 'sequential'.
+
+    Returns 'parallel' or 'sequential'.
+    """
+    # Special cases based on sub-action
+    if tool_name == "cronjob":
+        action = (tool_args or {}).get("action", "")
+        if action in _CRON_READ_ONLY:
+            return "parallel"
+        return "sequential"
+
+    if tool_name == "fact_store":
+        action = (tool_args or {}).get("action", "")
+        if action in ("search", "probe", "list", "related", "reason", "contradict"):
+            return "parallel"
+        return "sequential"
+
+    if tool_name == "memory":
+        action = (tool_args or {}).get("action", "")
+        if action in ("probe", "search", "list"):
+            return "parallel"
+        return "sequential"
+
+    # Check sequential first (more restrictive)
+    if tool_name in SEQUENTIAL_TOOLS:
+        return "sequential"
+
+    if tool_name in PARALLEL_SAFE_TOOLS:
+        return "parallel"
+
+    # Unknown tools default to sequential (safe)
+    return "sequential"
+
+
+def classify_batch(tool_calls: List[Dict]) -> Tuple[List[Dict], List[Dict]]:
+    """Split a list of tool calls into parallel-safe and sequential groups.
+
+    Args:
+        tool_calls: List of dicts with 'name' and 'args' keys
+
+    Returns:
+        (parallel_calls, sequential_calls)
+    """
+    parallel = []
+    sequential = []
+
+    for call in tool_calls:
+        name = call.get("name", "")
+        args = call.get("args", {})
+        classification = classify_tool_call(name, args)
+
+        if classification == "parallel":
+            parallel.append(call)
+        else:
+            sequential.append(call)
+
+    return parallel, sequential
+
+
+async def execute_parallel(
+    tool_calls: List[Dict],
+    executor: Callable,
+) -> List[Dict[str, Any]]:
+    """Execute parallel-safe tool calls concurrently.
+
+    Args:
+        tool_calls: List of tool call dicts
+        executor: Async callable(tool_name, tool_args) -> result
+
+    Returns:
+        List of results in same order as input
+    """
+    tasks = []
+    for call in tool_calls:
+        task = asyncio.create_task(
+            executor(call["name"], call.get("args", {})),
+            name=f"tool:{call['name']}"
+        )
+        tasks.append((call, task))
+
+    results = []
+    for call, task in tasks:
+        try:
+            result = await task
+            results.append({
+                "tool_name": call["name"],
+                "result": result,
+                "parallel": True,
+                "error": None,
+            })
+        except Exception as e:
+            logger.error("Parallel tool '%s' failed: %s", call["name"], e)
+            results.append({
+                "tool_name": call["name"],
+                "result": None,
+                "parallel": True,
+                "error": str(e),
+            })
+
+    return results
+
+
+async def execute_sequential(
+    tool_calls: List[Dict],
+    executor: Callable,
+) -> List[Dict[str, Any]]:
+    """Execute sequential tool calls one at a time."""
+    results = []
+    for call in tool_calls:
+        try:
+            result = await executor(call["name"], call.get("args", {}))
+            results.append({
+                "tool_name": call["name"],
+                "result": result,
+                "parallel": False,
+                "error": None,
+            })
+        except Exception as e:
+            logger.error("Sequential tool '%s' failed: %s", call["name"], e)
+            results.append({
+                "tool_name": call["name"],
+                "result": None,
+                "parallel": False,
+                "error": str(e),
+            })
+
+    return results
+
+
+async def execute_batch(
+    tool_calls: List[Dict],
+    executor: Callable,
+) -> BatchResult:
+    """Execute a batch of tool calls with parallel safety checks.
+
+    1. Classify each call as parallel-safe or sequential
+    2. Execute all parallel-safe calls concurrently
+    3. Execute sequential calls one at a time
+    4. Merge results in original order
+
+    Args:
+        tool_calls: List of dicts with 'name' and 'args' keys
+        executor: Async callable(tool_name, tool_args) -> result
+
+    Returns:
+        BatchResult with all results and timing
+    """
+    start = time.monotonic()
+
+    parallel_calls, sequential_calls = classify_batch(tool_calls)
+
+    # Execute parallel-safe calls concurrently
+    parallel_results = []
+    if parallel_calls:
+        parallel_results = await execute_parallel(parallel_calls, executor)
+
+    # Execute sequential calls in order
+    sequential_results = []
+    if sequential_calls:
+        sequential_results = await execute_sequential(sequential_calls, executor)
+
+    # Merge results — parallel first, then sequential (order preserved within groups)
+    all_results = parallel_results + sequential_results
+
+    elapsed = (time.monotonic() - start) * 1000
+
+    return BatchResult(
+        results=all_results,
+        parallel_count=len(parallel_calls),
+        sequential_count=len(sequential_calls),
+        elapsed_ms=elapsed,
+    )